Visual Prediction of Priors for Articulated Object Interaction

Exploration in novel settings can be challenging without prior experience in similar domains. However, humans are able to build on prior experience quickly and efficiently. Children exhibit this behavior when playing with toys. For example, given a toy with a yellow and blue door, a child will explore with no clear objective, but once they have discovered how to open the yellow door, they will most likely be able to open the blue door much faster. Adults also exhibit this behavior when entering new spaces such as kitchens. We develop a method, Contextual Prior Prediction, which provides a means of transferring knowledge between interactions in similar domains through vision. We develop agents that exhibit exploratory behavior with increasing efficiency, by learning visual features that are shared across environments, and how they correlate to actions. Our problem is formulated as a Contextual Multi-Armed Bandit where the contexts are images, and the robot has access to a parameterized action space. Given a novel object, the objective is to maximize reward with few interactions. A domain which strongly exhibits correlations between visual features and motion is kinemetically constrained mechanisms. We evaluate our method on simulated prismatic and revolute joints.Comment: IEEE International Conference on Robotics and Automation (ICRA) 202

Sun Protection Intervention for Urban Youth

Introduction: Skin cancer is less prevalent in persons with darker skin color compared to those with light skin, but contrarily is associated with greater mortality rates. Experts agree this is primarily due to late detection. Challenges in early detection include low public awareness, uncommon presentation, lower index of suspicion among health care providers, and decreased access to specialty care. To address some of these barriers, we designed a survey-based study to discover current beliefs, perceptions, and attitudes of urban youth towards sun protection before and after an educational intervention. Methods: In 2022, 17 children living in metro Detroit participated in an educational presentation regarding sun protection and completed pre- and post- surveys. Statistical significance was calculated via Chi-square tests. Results: After education, there was a significant increase in likelihood of sunscreen application before going outdoors (p \u3c 0.05). There was no significant difference after education regarding sunscreen beliefs (p = 0.463), sunscreen application frequency (p= 0.835), reapplication of sunscreen (p=1.074), daily sunscreen application (p=0.099), alternative sun protection (p=0.863), and likelihood of sharing about sun protection (p=0.227). Conclusions: This study was paired with a program that encouraged children to be active outside. The aim was to increase the likelihood of sunscreen application before going outdoors. In the pre-survey, more people said they would tell family and friends, but this was not reflected in the post survey. Future directions could include an interactive activity to share educational information and reinforce objectives

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Idealized Storytelling in interactive Role-Playing-Games

Diese Bachelorarbeit betrachtet die verschiedenen Formen des Storytellings in unterschiedlichen Medien. Dabei versucht diese Arbeit im Hauptteil zu klären, wie Storytelling klassisch funktioniert. Dabei geht sie auf Roman, Film und Videospiel ein. Im Schlussteil versucht der Verfasser zu erklären, was aus seiner Sicht „Ideales Storytelling“ ausmacht

Visual Prediction of Priors for Articulated Object Interaction

Exploration in novel settings can be challenging without prior experience in similar domains. However, humans are able to build on prior experience quickly and efficiently. Children exhibit this behavior when playing with toys. For example, given a toy with a yellow and blue door, a child will explore with no clear objective, but once they have discovered how to open the yellow door, they will most likely be able to open the blue door much faster. Adults also exhibit this behaviour when entering new spaces such as kitchens. We develop a method, Contextual Prior Prediction, which provides a means of transferring knowledge between interactions in similar domains through vision. We develop agents that exhibit exploratory behavior with increasing efficiency, by learning visual features that are shared across environments, and how they correlate to actions. Our problem is formulated as a Contextual Multi-Armed Bandit where the contexts are images, and the robot has access to a parameterized action space. Given a novel object, the objective is to maximize reward with few interactions. A domain which strongly exhibits correlations between visual features and motion is kinemetically constrained mechanisms. We evaluate our method on simulated prismatic and revolute joints